EKLAV: Elicited Key CoT Learning via Answer only superVision

EKLAV introduces a method to teach large language models complex reasoning skills using only answer-level supervision rather than full step-by-step reasoning traces. The system uses a specific prompting strategy and distillation process, resulting in improved performance on tasks requiring multi-step logic, demonstrating that answer supervision can effectively guide model learning.

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